Patents by Inventor Marwala Tshilidzi

Marwala Tshilidzi has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • System and method for real time prediction of water level and hazard level of a dam
    Patent number: 11769085
    Abstract: The invention relates to a water level prediction system for a dam. The system includes a water level prediction module which is configured to (a) receive time series data, which relates to a water level of the dam, in real-time; and (b) predict, in real-time, a future water level of the dam by processing the received time series data in one or more predictive models/formula(s)/algorithm(s). The one or more predictive models/formula(s)/algorithm(s) may include a recurrent neural network (RNN) or RNN model/algorithm which is configured/trained to predict, in real-time, a future water level of the dam by using the received time series data in the RNN or RNN model/algorithm. The water level prediction module may also include at least one statistical model/algorithm which is configured/trained to predict, in real-time, a future water level of the dam by using the received time series data in the statistical model/algorithm.
    Type: Grant
    Filed: May 22, 2019
    Date of Patent: September 26, 2023
    Assignee: UNIVERSITY OF JOHANNESBURG
    Inventors: Dipanjan Paul, Marwala Tshilidzi, Satyakama Paul
  • System and Method for Real Time Prediction of Water Level and Hazard Level of a Dam
    Publication number: 20210365761
    Abstract: The invention relates to a water level prediction system for a dam. The system includes a water level prediction module which is configured to (a) receive time series data, which relates to a water level of the dam, in real-time; and (b) predict, in real-time, a future water level of the dam by processing the received time series data in one or more predictive models/formula(s)/algorithm(s). The one or more predictive models/formula(s)/algorithm(s) may include a recurrent neural network (RNN) or RNN model/algorithm which is configured/trained to predict, in real-time, a future water level of the dam by using the received time series data in the RNN or RNN model/algorithm. The water level prediction module may also include at least one statistical model/algorithm which is configured/trained to predict, in real-time, a future water level of the dam by using the received time series data in the statistical model/algorithm.
    Type: Application
    Filed: May 22, 2019
    Publication date: November 25, 2021
    Applicant: UNIVERSITY OF JOHANNESBURG
    Inventors: Dipanjan Paul, Marwala Tshilidzi, Satyakama Paul